DeepSeek V3.1 vs Kimi K2.5
DeepSeek V3.1 (2025) and Kimi K2.5 (2026) compare a standalone API model against a coding-specialized model. DeepSeek V3.1 ships a 64k-token context window, while Kimi K2.5 ships a 256k-token context window. On MMLU PRO, Kimi K2.5 leads by 3.8 pts. On pricing, DeepSeek V3.1 costs $0.27/1M input tokens versus $0.44/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: DeepSeek V3.1 is standalone API model, while Kimi K2.5 is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | DeepSeek V3.1 | Kimi K2.5 |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | multimodal apps and provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, Agents, and Vision | Coding, RAG, and Agents |
| Context window | 64k | 256k |
| Cheapest output | $1/1M tokens | $2/1M tokens |
| Provider routes | 8 tracked | 10 tracked |
| Shared benchmarks | 2 shared | MMLU PRO leader |
Decision tradeoffs
- DeepSeek V3.1 has the lower cheapest tracked output price at $1/1M tokens.
- DeepSeek V3.1 uniquely exposes Code execution in local model data.
- Local decision data tags DeepSeek V3.1 for Coding, Agents, and Vision.
- Kimi K2.5 holds a shared-benchmark lead on MMLU PRO, ahead by 3.8 points.
- Kimi K2.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2.5 has broader tracked provider coverage for fallback and route flexibility.
- Kimi K2.5 uniquely exposes JSON / Tool use in local model data.
- Local decision data tags Kimi K2.5 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V3.1
$466
Cheapest tracked route/tier: Novita AI
Kimi K2.5
$852
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $386. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI, Together AI, and NVIDIA NIM; start route-level A/B tests there.
- Kimi K2.5 is $1/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Code execution before moving production traffic.
- Kimi K2.5 adds JSON / Tool use in local capability data.
- Provider overlap exists on Microsoft Foundry, Fireworks AI, and NVIDIA NIM; start route-level A/B tests there.
- DeepSeek V3.1 is $1/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for JSON / Tool use before moving production traffic.
- DeepSeek V3.1 adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-21 | 2026-03-15 |
| Context window | 64k | 256k |
| Parameters | 671B total, 37B active (MoE) | 1T (MoE, 384 experts) |
| Architecture | Mixture of Experts | Mixture of Experts |
| License | MITOSI-approved | Proprietary |
| Openness | Open source | Proprietary |
| Weights | Unknown | Not released |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V3.1 | Kimi K2.5 |
|---|---|---|
| Input price | $0.27/1M tokens | $0.44/1M tokens |
| Output price | $1/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.1 | Kimi K2.5 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| JSON / Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V3.1 | Kimi K2.5 |
|---|---|---|
| MMLU PRO | 83.3 | 87.1 |
| SWE-bench Verified | 66.0 | 76.8 |
Continue comparing
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.